Pykaldi: A Python Wrapper for Kaldi

By Dogan Can, Victor R. Martinez, Pavlos Papadopoulos, Shrikanth S. Narayanan. 2018

43 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Speech & Audio, Signal Processing

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. Juan Pino
2. Wei-Ning Hsu
3. Changhan Wang
4. Michael Auli
5. Alexei Baevski
6. Alexis Conneau
7. Yoshua Bengio
8. Jiatao Gu

In Speech & Audio

1. Wei-Ning Hsu
2. Alexis Conneau
3. Alexei Baevski
4. Michael Auli
5. Changhan Wang
6. Juan Pino
7. Yoshua Bengio
8. Mirco Ravanelli

In Signal Processing

1. Yoshua Bengio
2. Wei-Ning Hsu
3. Mirco Ravanelli
4. Alexei Baevski
5. Michael Auli
6. Alexis Conneau
7. Titouan Parcollet
8. James R. Glass

Citations in the corpus

• Unsupervised Speech Recognition (2021, methodology): “2) using PyKaldi (Can et al., 2018), a Python port of Kaldi (Povey et al.”
• Fairseq S2T: Fast Speech-to-Text Modeling with Fairseq (2020, methodology): “Data Pre-Processing FAIRSEQ S2T extracts Kaldi-compliant (Povey et al., 2011) speech features (e.g. log mel-filter banks) automatically from WAV/FLAC audio files via PyKaldi (Can et al., 2018) or torchaudio 1 .”
• The Pytorch-kaldi Speech Recognition Toolkit (2018, methodology): “PyKaldi [22], for instance, is an easy-to-use Python wrapper for the C++ code of Kaldi and OpenFst libraries.”